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Externalities in knowledge production: evidence from a randomized field experiment

Author

Listed:
  • Marit Hinnosaar

    (University of Nottingham
    Collegio Carlo Alberto
    CEPR)

  • Toomas Hinnosaar

    (University of Nottingham
    CEPR)

  • Michael E. Kummer

    (University of East Anglia
    Georgia Institute of Technology
    ZEW)

  • Olga Slivko

    (Erasmus University)

Abstract

Are there positive or negative externalities in knowledge production? We analyze whether current contributions to knowledge production increase or decrease the future growth of knowledge. To assess this, we use a randomized field experiment that added content to some pages in Wikipedia while leaving similar pages unchanged. We compare subsequent content growth over the next 4 years between the treatment and control groups. Our estimates allow us to rule out effects on 4-year growth of content length larger than twelve percent. We can also rule out effects on 4-year growth of content quality larger than four points, which is less than one-fifth of the size of the treatment itself. The treatment increased editing activity in the first 2 years, but most of these edits only modified the text added by the treatment. Our results have implications for information seeding and incentivizing contributions. They imply that additional content may inspire future contributions in the short- and medium-term but do not generate large externalities in the long term.

Suggested Citation

  • Marit Hinnosaar & Toomas Hinnosaar & Michael E. Kummer & Olga Slivko, 2022. "Externalities in knowledge production: evidence from a randomized field experiment," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 706-733, April.
    • Handle: RePEc:kap:expeco:v:25:y:2022:i:2:d:10.1007_s10683-021-09730-x
    DOI: 10.1007/s10683-021-09730-x
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    Cited by:

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    More about this item

    Keywords

    Knowledge accumulation; User-generated content; Wikipedia; Public goods provision; Field experiment;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • L17 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Open Source Products and Markets
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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